Vladimir G. Spokoiny

According to our database, Vladimir G. Spokoiny authored at least 29 papers between 2005 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Dimension-free bounds in high-dimensional linear regression via error-in-operator approach.

Fedor Noskov, Nikita Puchkin, Vladimir G. Spokoiny

CoRR, February, 2025

2023

Accelerated gradient methods with absolute and relative noise in the gradient.

Artem Vasin, Alexander V. Gasnikov, Pavel E. Dvurechensky, Vladimir G. Spokoiny

Optim. Methods Softw., November, 2023

Dimension Free Nonasymptotic Bounds on the Accuracy of High-Dimensional Laplace Approximation.

Vladimir G. Spokoiny

SIAM/ASA J. Uncertain. Quantification, September, 2023

2022

Structure-adaptive Manifold Estimation.

Nikita Puchkin, Vladimir G. Spokoiny

J. Mach. Learn. Res., 2022

Dimension free non-asymptotic bounds on the accuracy of high dimensional Laplace approximation.

Vladimir G. Spokoiny

CoRR, 2022

High dimensional change-point detection: a complete graph approach.

Yang-Wen Sun, Katerina Papagiannouli, Vladimir G. Spokoiny

CoRR, 2022

2020

Reinforced optimal control.

Christian Bayer, Denis Belomestny, Paul Hager, Paolo Pigato, John Schoenmakers, Vladimir G. Spokoiny

CoRR, 2020

2019

Adaptive Nonparametric Clustering.

Kirill Efimov, Larisa Adamyan, Vladimir G. Spokoiny

IEEE Trans. Inf. Theory, 2019

Online Graph-Based Change-Point Detection for High Dimensional Data.

Yang-Wen Sun, Katerina Papagiannouli, Vladimir G. Spokoiny

CoRR, 2019

2018

Pointwise adaptation via stagewise aggregation of local estimates for multiclass classification.

Nikita Puchkin, Vladimir G. Spokoiny

CoRR, 2018

2017

Random Gradient-Free Minimization of Convex Functions.

Yurii E. Nesterov, Vladimir G. Spokoiny

Found. Comput. Math., 2017

Earthquake prediction using the fields estimated by an adaptive algorithm.

Valeri G. Gitis, Alexander B. Derendyaev, Sergey A. Pirogov, Vladimir G. Spokoiny, E. F. Yurkov

Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics, 2017

2016

Convergence of an Alternating Maximization Procedure.

Andreas Andresen, Vladimir G. Spokoiny

J. Mach. Learn. Res., 2016

Detection of homologous recombination in closely related strains.

Anastasia S. Kalinina, Alexandra L. Suvorikova, Vladimir G. Spokoiny, Mikhail S. Gelfand

J. Bioinform. Comput. Biol., 2016

2015

Primal-Dual Methods for Solving Infinite-Dimensional Games.

Pavel E. Dvurechensky, Yurii E. Nesterov, Vladimir G. Spokoiny

J. Optim. Theory Appl., 2015

2014

Construction of Mean-Self-Financing Strategies for European Options under Regime-Switching.

G. N. Milstein, Vladimir G. Spokoiny

SIAM J. Financial Math., 2014

2013

Sparse non Gaussian component analysis by semidefinite programming.

Elmar Diederichs, Anatoli B. Juditsky, Arkadi Nemirovski, Vladimir G. Spokoiny

Mach. Learn., 2013

Uniform properties of the local maximum likelihood estimate.

Mayya M. Zhilova, Vladimir G. Spokoiny

Autom. Remote. Control., 2013

Properties of the posterior distribution of a regression model based on Gaussian random fields.

Alexey A. Zaitsev, Evgeny V. Burnaev, Vladimir G. Spokoiny

Autom. Remote. Control., 2013

2010

Sparse non-Gaussian component analysis.

Elmar Diederichs, Anatoli B. Juditsky, Vladimir G. Spokoiny, Christof Schütte

IEEE Trans. Inf. Theory, 2010

2008

Spatially Adaptive Estimation via Fitted Local Likelihood Techniques.

Vladimir Katkovnik, Vladimir G. Spokoiny

IEEE Trans. Signal Process., 2008

Diffusion tensor imaging: Structural adaptive smoothing.

Karsten Tabelow, Jörg Polzehl, Vladimir G. Spokoiny, Henning U. Voss

NeuroImage, 2008

A New Algorithm for Estimating the Effective Dimension-Reduction Subspace.

Arnak S. Dalalyan, Anatoli B. Juditsky, Vladimir G. Spokoiny

J. Mach. Learn. Res., 2008

2006

Recovering convex edges of an image from noisy tomographic data.

Alexander Goldenshluger, Vladimir G. Spokoiny

IEEE Trans. Inf. Theory, 2006

Analyzing fMRI experiments with structural adaptive smoothing procedures.

Karsten Tabelow, Jörg Polzehl, Henning U. Voss, Vladimir G. Spokoiny

NeuroImage, 2006

In Search of Non-Gaussian Components of a High-Dimensional Distribution.

Gilles Blanchard, Motoaki Kawanabe, Masashi Sugiyama, Vladimir G. Spokoiny, Klaus-Robert Müller

J. Mach. Learn. Res., 2006

Obtaining the Best Linear Unbiased Estimator of Noisy Signals by Non-Gaussian Component Analysis.

Masashi Sugiyama, Motoaki Kawanabe, Gilles Blanchard, Vladimir G. Spokoiny, Klaus-Robert Müller

Proceedings of the 2006 IEEE International Conference on Acoustics Speech and Signal Processing, 2006

A Novel Dimension Reduction Procedure for Searching Non-Gaussian Subspaces.

Motoaki Kawanabe, Gilles Blanchard, Masashi Sugiyama, Vladimir G. Spokoiny, Klaus-Robert Müller

Proceedings of the Independent Component Analysis and Blind Signal Separation, 2006

2005

Non-Gaussian Component Analysis: a Semi-parametric Framework for Linear Dimension Reduction.

Gilles Blanchard, Masashi Sugiyama, Motoaki Kawanabe, Vladimir G. Spokoiny, Klaus-Robert Müller

Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005